Course detail
Statistical Analysis and Experiment
FSI-9SAE Acad. year: 2024/2025 Winter semester
The course is intended for the students of doctoral degree programme and it is concerned with the modern methods of statistical analysis (random sample and its realization, distribution fitting and parameter estimation, statistical hypotheses testing, regression analysis) for statistical data processing gained at realization and evaluation of experiments in terms of students research work.
Language of instruction
Czech
Supervisor
Department
Entry knowledge
Rudiments of the probability theory and mathematical statistics.
Rules for evaluation and completion of the course
The exam is in form read report from choice area of statistical methods or else elaboration of written work specialized on solving of concrete problems.
Attendance at lectures is not compulsory, but is recommended.
Aims
The objective of the course is formalization of stochastic thinking of students and their familiarization with modern methods of mathematical statistics and possibilities usage of professional statistical software in research.
Students acquire higher knowledge concerning methods of mathematical statistics, which enable them to apply stochastic models of technical phenomena and processes by means calculations on PC.
The study programmes with the given course
Programme D-MAT-K: Materials Sciences, Doctoral, recommended course
Programme D-MAT-P: Materials Sciences, Doctoral, recommended course
Type of course unit
Lecture
20 hours, optionally
Syllabus
1. Probability distributions for modeling of technical phenomena and processes.
2. Exploratory analysis for statistical data processing.
3. Random sample – model and properties.
4. Search methods of probability distributions.
5. Estimation of probability distributions parameters.
6. Testing statistical hypotheses of distributions and of parameters.
7. Introduction to ANOVA, nonparametric tests.
8. Elements of linear regression analysis.
9. Statistical software – properties and option use.